code: def save_model(
      base_model: dict, file_name: str = "model.pkl"
  ) -> None:
      """
      Save pre-trained model on file system
      Args:
              base_model (dict): pre-trained model which is the output
                  of the fit function
              file_name (string): target file name as exact path.
      """
  
      model = base_model.copy()
  
      # modules cannot be saved. Save its reference instead.
      module_names = []
      for tree in model["trees"]:
          module_names.append(tree.__name__)
  
      model["trees"] = module_names
  
      with open(f"outputs/rules/{file_name}", "wb") as f:
          pickle.dump(model, f)
  
file_path: chefboost/chefboost/Chefboost.py
imports: import time
  import pickle
  import os
  import json
  from typing import Optional, Dict, Any, Union
  import numpy
  import pandas
  from chefboost.commons import functions, evaluate
  from chefboost.training import Training
  from chefboost.tuning import gbm, adaboost, randomforest
  from chefboost.commons.logger import Logger
label_desc: Use image node_id 3 for calling a global function with example usage: save_model(base_model, file_name) without return types